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In my previous post I was thinking about the fundamental components of a business. Now I want to think about the fundamental contexts and the four dimensions of each context.

Over the next few posts I will be exploring each of these contexts and dimensions. Personally, I think current data warehouse design is a load of bullshit. Relational business intelligence is an oxymoron.

I have been reflecting on the concept of creation and the concept of evolution for the past week. For most of history humanity has thought about a first cause and has attributed it to different gods. Gods were creators. In the west after a 1300 year dark age, around 1500AD, the renaissance led humanity to democratize creation. Humans took creativity away from gods and attributed to themselves as well. Then Charles Darwin came along.

Darwin had an even more humbling proposition. There was no creation. And as modern minds have considered Darwin’s theory they have been finding that there may be no origin, no direction, no destination and no constants to the universe at all. There is only change.

Until now humans have been clinging to the belief that they are creative. However, as we learn more about nature and human beings we are finding that humans have to accept that we are a product of and no different than the evolution that produced us. There is no origin, direction, destination or constants in our lives either. Anyone who claims certainty is no less gambling on life than anyone who accepts uncertainty.

Everything and everyone is unique and unintelligent. There are no creators and no designs. We have to democratize evolution.

We have to accept that we are all here for no other reason than evolution produced us. Darwin himself did not understand that there is no such thing as fitness. No one is more fit than anyone else because existence is arbitrary. Control is an illusion. All of humanity could cease to exist in a moment due to an unknown cosmic event.

So, when I look at people taking credit for anything or giving credit to a god, I am not persuaded at all. Because I know that they and all they produce as well as I and all I produce have no origin, no direction, no destination and no constants. Everyone is an impostor.

I have no need for guilt. No need for forgiveness. I can live as I wish. Quality and quantity of life are subjective. The motives and organization, events and locations, services and products, units and measures, currency and prices of life are arbitrary. Art and science, design and engineering, craft and trade, commerce and market are arbitrary. For all we do to alleviate our suffering there is always a new form of suffering to take its place.

I have been having a very interesting discussion on Linkedin.com having expressed my opinion about current information technology and the netular information technology I would like to see.

The people who have been exchanging their views with me cannot see the forest for the trees. One is offended that I do not rave about all the social transitions the technologies are offering. Another spews buzzwords like a chainsaw. Another assumes my opinion is a product of my impatience for the convergence of the existing technologies.

Einstein once said he would spend a majority of his time defining a problem and a fraction of his time solving it. A majority of the time on information technology is spent solving and a fraction actually taken to understand. The consequence is most of the solutions out there are not designed, they are hastily assembled patchworks that because of the inertia of being first on the field are only replaced by further patches.

Our entire system of networks is built upon a foundation of linear and tabular architecture that is present in our CPUs, memory, storage, data structures, programming languages, organization, locations, events and goals. In reality we are only dabbling in networks and doing an abysmal job of using them to their full effect. We don’t understand them.

Marshall McLuhan said that when a new media is created the first thing we do is pump old media through it. That is what we are doing now. We are taking every form of old media we have and pushing it through the internet. There is not a single case where we have successfully departed from linear and tabular old media. I have looked at all the current technology, I have used it, I understand its internals and I stand by what I say.

We need a fundamental change in the way information technology works otherwise we are going to continue with an undesigned brute force attempt to solve our problems without ever understanding them. The outcome will not be progress, but the perpetuation of flat earth thinking.

Linear and tabular thought are responsible for many of the problems we have in the world. The biggest is the inability to fully appreciate the uniqueness of everything and everyone in this world. The supreme example of this has been the long history of Religion, Genocide, Slavery, Nationalism, Imperialism, Racism, Eugenics, Fascism, Nazism, Communism, Marxism, Capitalism and Socialism. All of them fail us because they depended on linear and tabular models of thought that denied the respect of the individuality of all experience. True netular thought has the potential to challenge all of these misconceptions. I think it is appropriate that this transition is on the horizon with the rise of globalism. I doubt it will be a peaceful transition.

Actually, the insights into the underlying order in networks has made quite a bit of progress. One of the leaders in this area is Albert-Beszlos Barabasi who authored the book “Linked” http://www.nd.edu/~networks/Linked/index.html . Another researcher Kwabena Boahen made a fascinating presentation at TED http://tinyurl.com/6nnkb7 . There is also the work of Simon Williams that has come up with a new associative database architecture http://www.lazysoft.com as well as a commercial product, Sentences.

For years now I have been struggling with Relational DBMS technology and Associative DBMS technology attempting to get them to do what I want. In my first efforts, Relational models were structurally restrictive, Dimensional models were unable to grow organically, EAV models are incompatible with relational architecture. I came upon Simon Williams Associative Model of Data and although enthralled with its potential I found it too had limitations. It was semi-structured and allowed for too much flexibility. 25 years in Information Technology had taught me that there was a single standard classification system for setting up databases not a plethora of ontologies. I was determined to find the theoretical structure and was not concerned with hardware limitations, database architecture, abilties of current query languages or any other constraints.

The Associative Model of Data had made the difference in liberating me from Relational and Dimensional thinking. A traditional ERD of the Associative Model of Data I at first thought would look like the following:

Basically what you have is a Schema composed of Nodes with Node Associations through Verbs and Associations with Nodes Attributions through Verbs. The range of Node Entities, Verb Entities, Association Entities and Attribution Entities are endless. As well the population of the Schema has an unlimited dataset of natural key values. I have been challenged by Relational database specialists and SQL experts regarding the viability of this model within current limitations, however their arguments are irrelevant. What is important is the logical validity of the model, not the physical validity.

After receiving the criticism I decided to revisit the model in order to simplify it. I went over Simon William’s explanations of his model and its application and found I could reduce it to the following:

This was profoundly simpler and better reflected the Associative Model of Data’s Architecture. But even with this simpler architecture I was not satisfied. I felt that the Associatve Model although giving the benefit of explicitly defining the associations was a tabula rasa. Research has shown that tabula rasa’s are contrary to the behavior of the finite physical universe. There is an intermediate level of nature and nuture. And this is what I sought to model.

When I first encountered the Zachman Framework, something about it struck me in a very profound way. I could see there was something fundamental in its description of systems, however I felt that the metaphors that John Zachman used were wrong because they themselves lacked a fundamental simplicity. The consequences of this were that those who studied under Zachman ultimately could not agree on what he was talking about. Also the “disciplines” that Zachman’s Framework generated were continually reinventing the wheel. Zachman had created a world of vertical and horizontal stovepipes. To further the confusion Zachman refused to conceive of a methodology based upon his framework. Consequently, there was no way to determine what the priorities were in creating a system. I call this the Zachman Clusterfuck.

Zachman’s work spawned years of work for me. I could see that systems had a fundamental structure, but I could not agree with Zachman. Focuses and Perspectives were useless terms. The construction metaphor was useless. I read anything I could get my hands on dealing with systems, methodologies, modeling, networks and a broad range of other literature across the disciplines. Out of this came a set of conclusions:

There were a fundamental set of Noun Entities

There were a fundamental set of Verb Entities

There were a fundamental set of Association Entities

There was a clear order in which the Nouns were addressed

There was a clear order in which the Verbs were executed

The structure was fractal

The content was a scale-free network

I made some attempts at creating the vocabulary and experimented with this new Structured Thinking Language. However, the real break came when I worked with John Boyd’s OODA Loop:

The OODA Loop revealed a governing structure for the methodology and guided my way into the following hybrid relational/dimensional/associational model I call the Structured Associative Model of Data:

One of the key things this model demonstrates is the sequence followed by the OODA Loop. Starting from the top, each dimension set spawns the next. Choices are created from the dimensions. There is no centrism to this model which is an inherent flaw in Service Oriented Architecture (SOA), Event based architecture, Data centric architecture, Goal-Directed Design, Rule based systems among others. The stove pipes of Focuses and Pespectives disappear by reasserting a clear order of priorities and dependencies for achieving success. The model also supports bottom up inductive as well as top down deductive sequencing. This will make the system able to reconfigure to handle exceptions.

Some of the things I have learned in designing this model include the realization that unit defines datatype and that all measures are variable character string text. This is because any displayed value is only a symbolic representation of the actual quantity. If operations are to be performed on measures they are converted to the correct type as part of the operation. I also recognized that Unit was necessary to define the scale and scalability of the system. Further, it became apparent that analog calculations should not be practiced. Every value should be treated as discrete and aggregated.

Another aspect of this system is the inclusion of currency and amount. I have been critical of Zachman and academics for their hypocrisy regarding the economics of systems. All systems have a cost and a benefit and they are measurable in currency. Contrary to the reasoning of the majority, every decision is ultimately economic.

Tim Brown of IDEO has coined the term “Design Thinking” and has been toying with the concept for some time. Many designers dwell on the two dimensional concept of divergence and convergence as modes of thought. If we look at my model, divergence is the creation of choice while convergence is selection of choice. There is no alteration or deletion of choice in my model as history is preserved.

Now what you have is a unencumbered framework with a clear methodological sequence.

Tearing apart the Zachman Framework has yielded great results. I have identified the core nodes and links (we won’t use the terms entities and associations any more). The new Nodes of the Czerepak Framework are:

Computers

Machines

Goals

Observers

Elements

Particles

Points

Events

The new Links are:

Operations

Processes

Rules

Names

Bonds

Quanta

Distances

Durations

If you look at the link icons you can see what I am hypothesizing as the optimum cardinality for each. I am thinking about this from the perspective of the Platonic solids, R. Buckminster Fuller’s work, Stuart Koffman’s work with chaos theory and Boolean networks and Albert Einstein’s own love for geometry.

The nodes for the network graphics are Cause states, Observer states, Energy states, Mass states, Space states and Time states. To make this more relevant to business we can use the terms Goals, People, Functions, Data, Locations and Events. The edges that connect the nodes in all the networks are Cause rules, Observer rules, Energy rules, Mass rules, Space rules and Time rules. Nodes give the system its concepts, while edges give the system context. States provide extegrity (new term) while Rules provide integrity.

Each of the networks is composed of finite steps between the starting and terminal node called paths, the potential ways of following the rules to perform the steps are called the strategies, the actual strategy followed is called the tactics, the edges operations and the nodes are states .

Whether you are negotiating Goals, People, Functions, Data, Locations or Events, you have to create and observe the rules to maintain the integrity of the networks. Goals are connected by Rules, People are connected by Rules, Functions are connected by Rules, Data are connected by Rules, Locations are connected by Rules and Events are connected by Rules. Even Events (Time) is a network, because we are continuously referring to different clocks in different frames of reference.

All rules have the same characteristics:

We’ll explore how we will model this for each of the Six Hats, Six Coats networks in a subsequent post.

Now we have the connecting tissue of our networks. Knowing this, we can embark on a course to model all six networks separately. Once that is complete we can work on integrating two, three, four, five and finally all six networks into a single set of conventions.